In this work, we build an entity/event-level sentiment analysis system, which is able to recognize and infer both explicit and implicit sentiments among entities and events in the text. We design Probabilistic Soft Logic models to integrate explicit sentiments, inference rules, and +/-effect event information (events that positively or negatively affect entities) together. The experiments show that the method is able to greatly improve over baseline accuracies in recognizing entity/event-level sentiments.